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Cooperative EBM-AE Framework Combines Energy Refinement and Manifold Projection
A new arXiv paper proposes pairing an energy-based model with an autoencoder in a cooperative training setup. The method alternates between refining the learned energy landscape and projecting samples back onto a data manifold, aiming to overcome common training difficulties in energy-based generative models. The authors report the framework assigns low energy to realistic samples and higher energy to unlikely ones.